BACKGROUND:Anemia is a common complication in patients with chronic kidney disease (CKD), for which recombinant human erythropoietin (rhEPO) is the standard treatment. UB-851 is a biosimilar rhEPO developed as an alternative to epoetin alfa (Eprex ® ). This study evaluated the clinical equivalence, safety, and immunogenicity of UB-851 compared with epoetin alfa in patients with anemia due to CKD receiving hemodialysis. METHODS:In this 52-week, multicenter, randomized, parallel-group, phase III trial, patients with anemic CKD undergoing maintenance hemodialysis were assigned to receive either UB-851 or epoetin alfa. Part I (weeks 1-24) included dose titration and hemoglobin (Hb) maintenance. Part II (weeks 25-52) focused on long-term safety and immunogenicity. The primary endpoint was the change in Hb levels from baseline to the efficacy evaluation period (weeks 21-24). The secondary endpoints included epoetin dose, adverse events (AEs), and anti-drug antibody formation. RESULTS:A total of 201 participants were randomized, and the mean change in Hb levels during the efficacy period was within the predefined equivalence margin (±0.6 g/dL) in both the intention-to-treat and per-protocol populations. Differences in weekly epoetin dose changes between the groups also fell within the predefined equivalence range (±45 IU/kg/wk). No significant differences were observed in the laboratory parameters, electrocardiograms, or vital signs. No anti-epoetin antibodies were detected in the UB-851 group. Regarding AEs, the UB-851 appears to be biosimilar to epoetin alfa. CONCLUSION:UB-851 demonstrated clinical equivalence with epoetin alfa in maintaining Hb levels in patients with anemic CKD undergoing hemodialysis. The safety and immunogenicity profiles were comparable, supporting UB-851 as a biosimilar to epoetin alfa.

Individuals with chronic kidney disease are at increased risk for herpes zoster, cardiovascular events, kidney failure, and premature mortality. Although the recombinant zoster vaccine effectively prevents herpes zoster, its broader systemic effects in this population remain unclear. We conducted a retrospective cohort study of adults aged 50 years or older with incident chronic kidney disease using the U.S.-based TriNetX network from 2017 to 2024. A total of 13,218 vaccine recipients were propensity score-matched to 13,218 unvaccinated controls. The primary outcome was a kidney event, defined as progression to end-stage kidney disease or initiation of dialysis. Secondary outcomes included cardiovascular events and all-cause mortality. Cox proportional hazards models were used to estimate hazard ratios, with additional analyses of restricted mean survival time over five years and incidence rate differences. After a median follow-up of 3.0 years (IQR, 1.5-4.9), recombinant zoster vaccination was associated with significantly lower risks of kidney events (hazard ratio, 0.63; 95% CI, 0.57-0.70), cardiovascular events (hazard ratio, 0.74; 95% CI, 0.68-0.80), and all-cause mortality (hazard ratio, 0.51; 95% CI, 0.48-0.54). Greater risk reductions were observed among individuals who completed the two-dose series. These findings suggest that recombinant zoster vaccination in patients with chronic kidney disease is associated with substantial and sustained reductions in kidney disease progression, cardiovascular events, and mortality, supporting a potential role for vaccination in long-term cardiorenal protection.

BACKGROUND Central venous oxygen saturation (ScvO2), a biomarker that is well-correlated with arterial oxygen saturation, can predict mortality. Few studies have focused on blood volume, ScvO2, and mortality in patients on maintenance dialysis. This retrospective study used hospital record data of 144 dialysis patients with central venous catheter access (CVC) and aimed to evaluate the ScvO2 gradient, blood volume, and patient mortality. We examined the associations among absolute blood volume (ABV), mean ScvO2, intradialytic slope of ScvO2, and mortality in patients on dialysis. MATERIAL AND METHODS Adult patients receiving dialysis via CVC from 2022 to 2024 were enrolled. ScvO2, ABV, and protocol-based ultrafiltration were monitored using Crit-Line IV (Fresenius Medical Care, Bad Homburg, Germany). Participants were assessed and followed until death or administrative censor. Multiple fractional polynomial (MFP) regression was used to determine best-fitting polynomial function between predictors and mortality. We also constructed proportional hazard model to compare trends of ScvO2 for mortality. RESULTS In a total of 144 eligible patients, the incidence of mortality was 14.5 per 1000 patient-months. The correlation between mean ScvO2 and mortality was weak (r=-0.05), whereas the association between ABV change and mean ScvO2 were a reverse U curve. The intradialytic slope of ScvO2 was independently associated with mortality (adjusted odds ratio [95% CI]=0.421 [0.226-0.783], P<0.05). Those with descending slope of ScvO2 had higher risk of mortality than those with an ascending slope (HR [95% CI]=3.98 [1.22-13.03], P<0.05). CONCLUSIONS A negative trend of intradialytic ScvO2 was associated with mortality.

Background: This study investigated the discordance between cystatin C-and creatinine-based estimates of glomerular filtration rate (eGFR) (EKFCcys/EKFCcre) to predict adverse outcomes in older adults. Methods: Older patients with chronic kidney disease (CKD) (mean age 76.7) from 2018 to 2020 were enrolled. Cystatin C, creatinine, and clinical data were assessed at baseline and followed up until death, dialysis, or administrative censorship. The subjects were stratified according to tertiles of the EKFCcys/ EKFCcre ratio. The subhazard ratios (sHR) and time ratios were measured using competing risk regression and the cause-specific accelerated failure time (CS-AFT) model. Sensitivity analysis including models with cystatin-to-creatinine (Cys/Cre) ratios was also performed. Results: In 369 older patients, the incidence rates of mortality and dialysis were 2.7 and 7.0 per 1000 patient-months, respectively. The incidences of mortality and dialysis were higher in the lowest tertile (0.9 vs. 4.2 per 1000 patient-month and 6.1 vs. 7.0 per 1000 patient-months, respectively) than in the highest tertile group. In the competing risk regression, the lowest tertile had a higher risk of mortality (sHR [95% CI] = 6.78 [2.34-19.68], p < 0.05). In CS-AFT, compared to the highest tertile group, the lowest tertile group exhibited an altered median survival time of 0.27 (0.11-0.68) and 0.36 (0.20-0.67), which is approximately 73% and 64% decrease in median survival time to mortality and dialysis, respectively (ps < 0.05). The results of the sensitivity tests were consistent. Conclusion: The lowest tertile of the cystatin C-to-creatinine based eGFR ratio is a risk factor for clinical outcomes in older patients with CKD. Copyright (c) 2025, Taiwan Society of Geriatric Emergency & Critical Care Medicine.

Purpose: Per- and polyfluoroalkyl substances (PFAS) comprise a class of man-made compounds widely utilized in manufacturing everyday consumer products. Experimental studies indicate that PFAS may interfere with iron regulation by hindering absorption or inducing oxidative stress. Nonetheless, epidemiological studies examining the association between PFAS exposure and a broad spectrum of iron-related biomarkers remain scarce. Approach and Results: In this study, data from the 2013–2018 National Health and Nutrition Examination Survey (NHANES) were analyzed, which included 5050 adults aged 18 and older. The relationships between six PFAS compounds, oral iron intake, and a comprehensive set of markers of iron homeostasis, including serum iron, unsaturated iron-binding capacity (UIBC), total iron-binding capacity (TIBC), transferrin saturation, ferritin, and transferrin receptor levels, were examined. Our findings revealed a negative association between both individual and total PFAS (sum of six PFAS) levels and oral iron intake. Additionally, serum iron and transferrin saturation levels exhibited significant positive correlations with all PFAS compounds, whereas ferritin was positively correlated with all PFAS compounds except n-perfluorooctanoic acid (n-PFOA). UIBC and transferrin receptor showed significant negative correlations with all PFAS compounds, while TIBC was significantly negatively correlated with n-perfluorooctane sulfonic acid (n-PFOS), perfluoromethylheptane sulfonic acid isomers (sm-PFOS), perfluorohexane sulfonic acid (PFHxS), and the total PFAS. Conclusions: Higher PFAS exposure was associated with altered iron status biomarkers While this cross-sectional study cannot establish causality, the observed associations raise the possibility that PFAS exposure may influence iron absorption. These findings emphasize the need for additional research into the potential impact of PFAS exposure on iron homeostasis.

Background:Diabetic nephropathy (DN), a severe complication of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease. The International Diabetes Federation projects that by 2045, 783 million people will have diabetes, with 30%-40% of them developing DN. Current diagnostic approaches lack sufficient sensitivity and specificity for early detection and diagnosis, underscoring the need for an accurate, interpretable predictive model to enable timely intervention, reduce cardiovascular risks, and optimize health care costs. Objective:This study aimed to develop and validate a machine learning-based predictive model for DN in patients with type 2 diabetes, with a focus on achieving high predictive accuracy while ensuring transparency and interpretability through explainable artificial intelligence techniques, thereby supporting early diagnosis, risk assessment, and personalized clinical decision-making. Methods:Our retrospective cohort study investigated 1000 patients with type 2 diabetes using data from electronic medical records collected between 2015 and 2020. The study design incorporated a sample of 444 patients with DN and 556 without, focusing on demographics, clinical metrics such as blood pressure and glucose levels, and renal function markers. Data collection relied on electronic records, with missing values handled via multiple imputation and dataset balance achieved using Synthetic Minority Oversampling Technique (SMOTE). In this study, advanced machine learning algorithms, namely Extreme Gradient Boosting (XGBoost), CatBoost, and Light Gradient-Boosting Machine (LightGBM), were used due to their robustness in handling complex datasets. Key metrics, including accuracy, precision, recall, F1-score, specificity, and area under the curve, were used to provide a comprehensive assessment of model performance. In addition, explainable machine learning techniques, such as Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive Explanations (SHAP), were applied to enhance the transparency and interpretability of the models, offering valuable insights into their decision-making processes. Results:XGBoost and LightGBM demonstrated superior performance, with XGBoost achieving the highest accuracy of 86.87%, a precision of 88.90%, a recall of 84.40%, an F1-score of 86.44%, and a specificity of 89.12%. LIME and SHAP analyses provided insights into the contribution of individual features to elucidate the decision-making processes of these models, identifying serum creatinine, albumin, and lipoproteins as significant predictors. Conclusions:The developed machine learning model not only provides a robust predictive tool for early diagnosis and risk assessment of DN but also ensures transparency and interpretability, crucial for clinical integration. By enabling early intervention and personalized treatment strategies, this model has the potential to improve patient outcomes and optimize health care resource usage.

UNSTRUCTURED:Introduction: Diabetic Nephropathy (DN), a severe complication of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease. The International Diabetes Federation projects that by 2045, 783 million people will have diabetes, with 30%-40% of them developing DN. Current diagnostic approaches lack sufficient sensitivity and specificity for early detection and diagnosis, underscoring the need for an accurate, interpretable predictive model to enable timely intervention, reduce cardiovascular risks, and optimize healthcare costs. Methods: Our retrospective cohort study investigated 1,000 type-2 diabetes patients using data from electronic medical records collected between 2015 and 2020. The study design incorporated a sample of 444 patients with diabetic nephropathy and 556 without, focusing on demographics, clinical metrics such as blood pressure and glucose levels, and renal function markers. Data collection relied on electronic records, with missing values handled via multiple imputation and dataset balance achieved using SMOTE. In this study, advanced machine learning algorithms, namly XGBoost, CatBoost, and LightGBM, were utilized due to their robustness in handling complex datasets. Key metrics, including accuracy, precision, recall, F1 score, specificity, and area under the curve (AUC), were employed to provide a comprehensive assessment of model performance. Additionally, Explainable Machine Learning (XML) techniques, such as LIME and SHAP, were applied to enhance the transparency and interpretability of the models, offering valuable insights into their decision-making processes. Results: XGBoost and LightGBM demonstrated superior performance, with XGBoost achieving the highest accuracy of 86.87%, a precision of 88.90%, a recall of 84.40%, an f1 score of 86.44%, and a specificity of 89.12%. LIME and SHAP analyses provided insights into the contribution of individual features to elucidate the decision-making processes of these models, identifying serum creatinine, albumin, and lipoproteins as significant predictors. Conclusion: The developed machine learning model not only provides a robust predictive tool for early diagnosis and risk assessment of DN but also ensures transparency and interpretability, crucial for clinical integration. By enabling early intervention and personalized treatment strategies, this model has the potential to improve patient outcomes and optimize healthcare resource utilization.

The comparative effectiveness of finerenone and spironolactone in chronic kidney disease (CKD) with type 2 diabetes (T2D) remains unclear. Here we show, using a target trial emulation on global real-world data from TriNetX, outcomes among 2268 propensity score-matched adults with CKD (eGFR 15-60 mL/min/1.73 m²) and T2D who initiated finerenone or spironolactone between July 2021 and September 2024. Over a median follow-up of 1.3 years, finerenone is associated with lower risks of major adverse cardiovascular events (adjust hazard ratio [aHR], 0.74; 95% CI, 0.58-0.94), major adverse kidney events (aHR, 0.47; 95% CI, 0.33-0.67), all-cause mortality (aHR, 0.31; 95% CI, 0.21-0.45), and hyperkalemia (17.2% vs. 26.4%; P < 0.001) compared with spironolactone. These findings suggest potential benefits of finerenone over spironolactone in reducing mortality and cardiorenal risk among patients with CKD and T2D.

Monoterpenes are organic compounds which have been studied for their medicinal benefits. However, the association between monoterpene exposure and metabolic parameters in humans is unknown. We investigated the connection between three specific monoterpenes (α-pinene, β-pinene, and limonene), glucose homeostasis biomarkers, lipid profiles, and metabolic syndrome (MS) in 1627 adults from the National Health and Nutrition Examination Survey (NHANES) 2013–2014. We found serum levels of α-pinene and β-pinene were positively associated with fasting glucose, total cholesterol, triglyceride, and apolipoprotein B. In addition, increased levels of limonene and Σmonoterpene (sum of three monoterpene chemicals) were linked to higher insulin, β-cell function, total cholesterol, low density lipoprotein cholesterol (LDL-C), triglycerides, and apolipoprotein B. Participants with all three monoterpenes above the 50th percentile had notably higher values for total cholesterol and triglycerides compared to those with all three monoterpenes below the 50th percentile (P for trend <0.001). Regarding MS, higher serum concentrations of α-pinene were linked to an increased risk of high-density lipoprotein cholesterol (HDL-C) insufficiency and hypertriglyceridemia. Elevated concentrations of β-pinene were associated with a higher prevalence of hypertriglyceridemia. Moreover, increased levels of limonene and Σmonoterpene were connected to a higher risk of MS, larger waist circumference, low HDL-C, hypertriglyceridemia, and higher blood pressure according to MS criteria. In conclusion, serum monoterpenes levels were linked to glucose regulation, lipid profiles, and indicators of MS. Further studies are necessary to clarify the potential causal relationships.

Magnetic nanoparticles (MNPs) have been widely utilized in the biomedical field for numerous years, offering several advantages such as exceptional biocompatibility and diverse applications in biology. However, the existing methods for quantifying magnetic labeled sample assays are scarce. This research presents a novel approach by developing a microfluidic chip system embedded with a giant magnetoresistance (GMR) sensor. The system successfully detects low concentrations of MNPs with magnetic particle velocities of 20 mm/s. The stray field generated by the magnetic subject flowing through the microchannel above the GMR sensor causes variations in the signals. The sensor's output signals are appropriately amplified, filtered, and processed to provide valuable indications. The integration of the GMR microfluidic chip system demonstrates notable attributes, including affordability, speed, and user-friendly operation. Moreover, it exhibits a high detection sensitivity of 10 μg/μL for MNPs, achieved through optimizing the vertical magnetic field to 100 Oe and the horizontal magnetic field to 2 Oe. Additionally, the study examines magnetic labeled RAW264.7 cells. This quantitative detection of magnetic nanoparticles can have applications in DNA concentration detection, protein concentration detection, and other promising areas of research.

Purpose: Di-(2-ethylhexyl) phthalate (DEHP) has been utilized in many daily products for decades. Previous studies have reported that DEHP exposure could induce renin–angiotensin–aldosterone system activation and increase epithelial sodium channel (ENaC) activity, which contributes to extracellular fluid (ECF) volume expansion. However, there is also no previous study to evaluate the association between DEHP exposure and body fluid status. Methods: We selected 1678 subjects (aged ≥18 years) from a National Health and Nutrition Examination Survey (NHANES) in 2003–2004 to determine the relationship between urine DEHP metabolites and body composition (body measures, bioelectrical impedance analysis (BIA)). Results: After weighing the sampling strategy in multiple linear regression analysis, we report that higher levels of DEHP metabolites are correlated with increases in body measures (body weight, body mass index (BMI), waist circumference), BIA parameters (estimated fat mass, percent body fat, ECF, and ECF/intracellular fluid (ICF) ratio) in multiple linear regression analysis. The relationship between DEHP metabolites and the ECF/ICF ratio was more evident in subjects of younger age (20–39 years old), women, non-Hispanic white ethnicity, and subjects who were not active smokers. Conclusion: In addition to being positively correlated with body measures and body fat, we found that urine DEHP metabolites were positively correlated with ECF and the ECF/ICF ratio in the US general adult population. The finding implies that DEHP exposures might increase ECF volume and the ECF/ICF ratio, which may have adverse health outcomes on the cardiovascular system. Further research is needed to clarify the causal relationship.

The levels of fibroblast growth factor 23 (FGF23) rapidly increases after acute kidney injury (AKI). However, the role of FGF23 in AKI is still unclear. Here, we observe that pretreatment with FGF23 protein into ischemia-reperfusion induced AKI mice ameliorates kidney injury by promoting renal tubular regeneration, proliferation, vascular repair, and attenuating tubular damage. In vitro assays demonstrate that SDF-1 induces upregulation of its receptor CXCR4 in endothelial progenitor cells (EPCs) via a non-canonical NF-κB signaling pathway. FGF23 crosstalks with the SDF-1/CXCR4 signaling and abrogates SDF-1-induced EPC senescence and migration, but not angiogenesis, in a Klotho-independent manner. The downregulated pro-angiogenic IL-6, IL-8, and VEGF-A expressions after SDF-1 infusion are rescued after adding FGF23. Diminished therapeutic ability of SDF-1-treated EPCs is counteracted by FGF23 in a SCID mouse in vivo AKI model. Together, these data highlight a revolutionary and important role that FGF23 plays in the nephroprotection of IR-AKI.

Acute kidney injury (AKI) is a common syndrome that has a significant impact on prognosis in various clinical settings. To evaluate whether new evidence supports changing the current definition/classification/staging systems for AKI suggested by the Kidney Disease: Improving Global Outcomes (KDIGO) 2012 Clinical Practice Guideline, the Taiwan AKI-TASK Force, composed of 64 experts in various disciplines, systematically reviewed the literature and proposed recommendations about the current nomenclature and diagnostic criteria for AKI. The Taiwan Acute Kidney Injury (TW-AKI) Consensus 2020 was established following the principles of evidence-based medicine to investigate topics covered in AKI guidelines. The Taiwan AKI-TASK Force determined that patients with AKI have a higher risk of developing chronic kidney disease, end-stage renal disease, and death. After a comprehensive review, the TASK Force recommended using novel biomarkers, imaging examinations, renal biopsy, and body fluid assessment in the diagnosis of AKI. Clinical issues with regards to the definitions of baseline serum creatinine (sCr) level and renal recovery, as well as the use of biomarkers to predict renal recovery are also discussed in this consensus. Although the present classification systems using sCr and urine output for the diagnosis of AKI are not perfect, there is not enough evidence to change the current criteria in clinical practice. Future research should investigate and clarify the roles of the aforementioned tools in clinical practice for AKI.

The multi-functional micelles poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide-co-10 undecanoic acid)/CM-Dextran Fe3O4 (PNDU/CM-Dex Fe3O4) were poly (NIPAAm-co-DMAAm-co-UA) (PNDU) grafting hydrophilic CM-Dextran Fe3O4 which possess pH-dependent temperature response and magnetic response. In this research, anti-inflammation drug Hesperetin was encapsulated by micelles using membrane dialysis method to obtain the different ratio of Hesperetin-embedded P5DF10, P10DF10, and P20DF10. These micelles were characterized by Fourier transform infrared spectroscopy, 1H-NMR, thermogravimetric analyzer, and superconducting quantum interference device magnetometer. The morphology and particle size of micelles was observed by transmission electron microscopy and dynamic light scattering. The low critical solution temperature of the P10DF10 micelles is in pH 6.6 at about 37.76°C and in pH 7.4 at about 41.70°C. The biocompatibility of micelles was confirmed by cytotoxicity study. Inflammatory inhibition of hesperetin-embedded P10DF10 micelles also studied through RAW264.7. Hesperetin-embed P10DF10 micelles suppressed LPS-induced inflammatory response. Via immunofluorescence cell staining demonstrate that Hesperetin-embed P10DF10 micelles inhibited the activation of NF-κB p60 and markedly attenuated in a drug dose-dependent manner. At a concentration of 1,000 ug/ml, an inflammatory rate can be reduced to 36.9%. Based on these results, the hesperetin-embed P10DF10 micelles had successfully synthesized and enable to carry and release the anti-inflammatory drugs, which instrumental for biomedical therapy and applications.

OBJECTIVE The saline infusion test (SIT) and the captopril test (CT) are widely used as confirmatory tests for primary aldosteronism (PA). We hypothesized that post-SIT and post-CT plasma aldosterone concentrations (PAC) indicate the severity of aldosterone-producing adenoma (APA) and might predict clinical outcome. METHODS We recruited 216 patients with APA in the Taiwan Primary Aldosteronism Investigation (TAIPAI) registry who received both seated SIT and CT as confirmatory tests. The data of 143 patients who underwent adrenalectomy with complete follow-up after diagnosis were included in the final analysis. We determined the proportion of patients achieving clinical success in accordance with the Primary Aldosteronism Surgical Outcome consensus. Logistic regression analysis was conducted to identify preoperative factors associated with cure of hypertension. RESULTS Complete clinical success was achieved in 48 (33.6%) patients and partial clinical success in 59 (41.2%) patients; absent clinical success was seen in 36 (25.2%) of 143 patients. Post-SIT PAC but not post-CT PAC was independently associated with clinical outcome. Higher levels of post-SIT PAC had a higher likelihood of clinical benefit (complete plus partial clinical success; odds ratio = 1.04 per ng/dl increase, 95% confidence interval = 1.01, 1.06; P = 0.004). Patients with post-SIT PAC > 25 ng/dl were more likely to have a favorable clinical outcome after adrenalectomy. This cutoff value translated into a positive predictive value of 86.0%. CONCLUSIONS We suggest that post-SIT PAC is a better predictor than post-CT PAC for clinical success in PA post adrenalectomy.

Lead exposure has been suspected as a risk factor for osteoporosis. However, in epidemiological studies, the association between environmental lead exposure and bone health were inconsistent. With the decrease of lead exposure in recent decades, we evaluated the association between lead exposure and bone mineral density (BMD) in the general US population in this study. We analyzed data on 1859 adults (aged ≥40 years) from the National Health and Nutrition Examination Survey (NHANES) conducted in 2013-2014 to determine the relationship among lead exposure measured by both blood and urine lead concentration, BMD of total spine and femur, and FRAX score in a cross-sectional study. In premenopausal women, the results showed a 1-unit increase in natural log-transformed blood and urine lead levels was associated with a decrease in total femur BMD of 0.061 g/cm2 (S.E. = 0.015; p = 0.001) and 0.046 g/cm2 (S.E. = 0.018; p = 0.020), respectively. Moreover, in premenopausal women, a 1-unit increase in natural log-transformed blood level was associated with a decrease in total spine BMD of 0.054 g/cm2 (S.E. = 0.019; p = 0.013). Both FRAX scores were positively correlated with blood and urine lead levels in subjects without fractures, while the 10-year hip fracture risk score was positively associated with lead exposure in subjects with a history of fracture or vertebral fracture. In conclusion, lead exposure was associated with decreased total femur and spine BMD, and FRAX score in the general US population. Further research is needed to elucidate the causal relationship among lead exposure, BMD, and fracture risk.

Acute kidney injury (AKI) can be caused by various factors such as toxins, ischemia, sepsis, obstructive uropathy, and others. Currently, there are two main classification systems that are used for determination of AKI severity in clinical practice, and these are the Risk/Injury/Failure/Loss/End-stage (RIFLE) criteria and Acute Kidney Injury Network (AKIN) criteria. Both have implemented the rise of creatinine level and decreased in urine output as two major factors in determining the severity of AKI and act as a guide to start renal replacement therapy (RRT). However, none of the classification systems have implicated AKI duration as another dimension for defining the true severity of kidney dysfunction.

Acute kidney injury (AKI) is detrimental after cardiac surgery. In this multicenter study, the novel biomarker hemojuvelin (HJV) was evaluated for AKI prediction following cardiac surgery. Urinary HJV, neutrophil gelatinase-associated lipocalin (NGAL), and urinary creatinine were measured in 151 patients after surgery. The outcomes of advanced AKI (KDIGO stages 2 and 3) and all causes of in-hospital mortality as the composite outcome were recorded. Areas under the receiver operator characteristic curves (AUC) and a multivariate generalized additive model (GAM) were applied to predict these outcomes of interest. Urinary HJV differentiated patients with/without AKI, advanced AKI or composite outcome after surgery (p < 0.001, by a generalized estimating equation) in this study. At three hours post-surgery, urinary HJV predicted advanced AKI (p < 0.001) and composite outcome (p < 0.001) with corresponding AUC values of 0.768 and 0.828, respectively. The performance of creatinine-adjusted HJV was also superior to NGAL in predicting advanced AKI (AUC = 0.784 and 0.694; p = 0.037) and composite outcome (AUC = 0.842 and 0.676; p = 0.002). The integration of HJV into the Cleveland Clinic score for advanced AKI led to a significant increase in risk stratification (net reclassification improvement [NRI] = 0.598; p < 0.001).

ObjectivesThis study examines the associations between total testosterone levels and dialysis mortality.MethodsElderly men who initiate hemodialysis in Taoyuan General Hospital from January 2012 to June 2017 were enrolled. We reviewed clinical characteristics and biochemical data from start of dialysis and followed over a 5‐year period after dialysis. Body composition parameters were assessed 3‐6 months after dialysis. Skeletal muscle mass index (SMMI) was defined by skeletal muscle mass divided by squared height. We defined those with lowest tertile of testosterone values as low testosterone group. Adjusted hazard ratios (aHRs) and 95% confidence interval (95% CI) for mortality and cumulative survival curves were evaluated by Cox hazards model and Kaplan‐Meier method. The discriminative power of SMMI and testosterone levels was calculated according to the area under the curve and the receiver operating characteristic curve (AUROC).ResultsFrom a total of 137 elderly hemodialysis patients, the range of lowest, middle, and highest tertile of testosterone values was <6.25 nmol/L, 6.25‐10.5 nmol/L, and >10.5 nmol/L. After multivariate adjustment other than SMMI, total testosterone levels at baseline were a significant predictor for mortality aHR(95% CI): 0.79 (0.70‐0.91). The unadjusted and adjusted c‐statistics of SMMI vs testosterone values to predict overall were 770 (0.688‐0.852) vs 0.779 (0.691‐0.866) and 855 (0.812‐0.886) vs 0.812 (0.744‐0.856) (Ps < .05), whereas the capacity of c‐statistics was similar (χ2 = 0.143 and 2.709, Ps > .05).ConclusionsTotal testosterone value was a predictor for mortality. It was noninferior to SMMI in predicting dialysis mortality.